A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. This slide is all about a detailed description of the Face Recognition System.

1. Presented By-Rahul Singh
CSE 3rd Year
College-Nitra Technical Campus Ghaziabad
Linkedin - https://www.linkedin.com/in/rahul-singh-
171b77156/


2. Outline-
 1. Introduction
 2. Biometrics
 3. History
 4. Facial Recognition
 5. Implementation
 6. How it works
 7. Strengths & Weaknesses
 8. Applications
 9. Conclusion
 10. Refrences

3. Introduction
 Everyday actions are increasingly being
handled electronically, instead of pencil and
paper or face to face.
 This growth in electronic transactions
results in great demand for fast and accurate
user identification and authentication.

4. Biometrics
 A biometric is a unique, measurable characteristic of a
human being that can be used to automatically
recognize an individual or verify an individual’s
identity.
 Biometrics can measure both physiological and
behavioral characteristics.
 Physiological biometrics:- This biometrics is based on
measurements and data derived from direct
measurement of a part of the human body.
 Behavioral biometrics:- this biometrics is based on
measurements and data derived from an action

5. Type of biometrics

6. What is face recognition system ?

7.  A facial recognition system is a technology
capable of identifying or verifying a person
from a digital image or a video frame from
a video source.
 It requires no physical interaction on
behalf of the user.
 It is accurate and allows for high
enrolment and verification rates.
 It can use your existing hardware
infrastructure, existing camaras and image
capture Devices will work with no
problems

8. History
 In 1960s, the first semi-automated system for facial
recognition to locate the features(such as eyes, ears,
nose and mouth) on the photographs.
 In 1970s, Goldstein and Harmon used 21 specific
subjective markers such as hair color and lip thickness
to automate the recognition.
 In 1988, Kirby and Sirovich used standard linear
algebra technique, to the face recognition. 03/12/13 8

9. Facial Recognition
 VERIFICATION- The system compares the given
individual with who they say they are and gives a yes or
no decision.
 IDENTIFICATION- The system compares the given
individual to all the Other individuals in the database
and gives a ranked list of matches.

10. Identification
 All identification or authentication technologies operate
using the following four stages:
 Capture: A physical or behavioural sample is captured by
the system during Enrollment and also in identification or
verification process.
 Extraction: unique data is extracted from the sample and a
template is created.
 Comparison: the template is then compared with a new
sample.
 Match/non-match: the system decides if the features
extracted from the new Samples are a match or a non
match.

11. Implimentation
The implementation
of face recognition
technology includes
the following four
stages:
• Image acquisition
• Image processing
•Face image
classification
• Decision making

12. Image acquisition

13. Image Processing
 Images are cropped such
that the ovoid facial
image remains, and color
images are normally
converted to black and
white in order to
facilitate initial
comparisons based on
grayscale characteristics.

14. Distinctive characteristic
location
 All facial-scan systems
attempt to match visible
facial features in a
fashion similar to the
way people recognize
one another.

15. Template creation

16. Template matching
 It compares match templates against enrollment
templates.
 • A series of images is acquired and scored against
the enrollment, so that a user attempting 1:1
verification within a facial-scan system may have
10 to 20 match attempts take place within 1 to 2
seconds.

17. How Facial Recognition System
Works

18. Strengths
 It is the only biometric able to operate without user cooperation.
 Anywhere that you can put a camera, you can potentially use a facial
recognition system. Many cameras can be installed throughout a
location to maximize security coverage without disrupting traffic
flow.
 Face recognition systems can be installed to require a person to
explicitly step up to a camera and get their picture taken, or to
automatically survey people as they pass by a camera. The later
mode allows for scanning of many people at the same time
 Video or pictures can be replayed through a facial recognition system
for surveillance or forensics work after an event.
 Face scanning is not noticeable, can be done at a comfortable
distance and does not require the user to touch anything.

19. Weaknesses
 Changes in acquisition environment reduce
matching accuracy.
 Changes in physiological characteristics
reduce matching accuracy.
 It has the potential for privacy abuse due to
non co-operative enrollment and
identification capabilities.
 Such systems may be fooled by hats, beards,
sunglasses and face masks.

20. Applications
 Banking using ATM
 Voter verification
 Residential/office
Security:
 Security/Counterterroris
m
 Smart Security system

21. Application
 Apple iPhone X uses
Face id technology.

22. Applications:Video Demo

23. Conclusion
 For implementations where the biometric
system must verify and identify users
reliably over time, facial scan can be a very
difficult, but not impossible, technology to
implement successfully.

24. In National Security
Show of hands, who
believe this system
would work to catch
terrorists and criminals

25. Reference-
 Wikipedia
 Slide Share
 Google-for images
 Tutorialpoint.com